Application of deep-learning based approach for OFDM system

In comparison to other modulation techniques, Orthogonal frequency-division multiplexing (OFDM) techniques are widely used for wireless communications. It has high spectral efficiency, is immune to impulse interference, and can handle very strong echoes. However, channel estimation and signal detect...

Full description

Saved in:
Bibliographic Details
Main Author: Zhang, Yutong
Other Authors: Teh Kah Chan
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
Subjects:
Online Access:https://hdl.handle.net/10356/158302
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
Description
Summary:In comparison to other modulation techniques, Orthogonal frequency-division multiplexing (OFDM) techniques are widely used for wireless communications. It has high spectral efficiency, is immune to impulse interference, and can handle very strong echoes. However, channel estimation and signal detection are difficult for OFDM system without cyclic prefix. Therefore, the aim of this report is to design an AI receiver to estimate channels and detect channels of OFDM system. The accuracy of the model will be tested by comparing the Bit-error rate (BER) of simulation results. The network model was built by using python.